Adgully Bureau
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Authored By: Paritosh Gandhi, Country Head, India, Infobip
Today’s customers live in a perpetually connected world, switching devices, apps, and even locations mid‑journey. At the same time, they expect brands to remember who they are and what they need in real time.Nearly 98%of customer journeys today touch more than one channel. This makes single‑channel customer communication effectively obsolete for serious brands.
However, while96%of organizations already automate customer communications and more than half have adopted agentic AI for use‑case automation, many still struggle to make these interactions truly conversational and effective in practice. This “effectiveness gap” is stark. The question is no longer whether enterprises are using AI, but whether they are using it to build relationships – or merely to send more notifications.
For many enterprises, AI still appears as “a chatbot on a website” or a recommendation engine hidden in the background. In reality, advanced AI models go beyond chatbots, using multiple AI agents across use cases such as logistics, transactions, and support, with the ability to understand intent, sentiment, and context across chat, voice, and social channels. These agents can proactively guide customers through discovery, purchase, onboarding, and support, and can hand over to human agents with full context – from previous messages to transaction history – so that customers do not have to repeat themselves at every touchpoint.
A decade ago,roughly 73%of traffic was single‑channel. Today, only around 2-3% remains so, with AI‑powered, omnichannel conversations becoming the norm. In India, WhatsApp has emerged as a key home of conversational commerce and service. However, the most resilient strategies combine WhatsApp, RCS, SMS, email, in‑app messaging and voice into one orchestrated experience, rather than betting on a single channel alone.
Closing the AI CX maturity gap
Onlyaround 27%of brands use a true orchestration platform, even though half are already API‑ready. This means many enterprises already have the technical building blocks for AI‑led customer engagement, but not the connected infrastructure needed to make it seamless. That’s why the effectiveness gap persists. There are several structural issues at play, right from disconnected tools to enormous data silos slowing down automation and optimization.
To address these issues, the blueprint forward is clear:
- Unify data and channels on one AI‑first cloud communications platform, centralizing customer profiles, events, and preferences across SMS, RCS, WhatsApp, email, in‑app messaging, and voice.
- Design customer journeys on a “human + machine” principle: let AI agents handle repetitive, high‑volume tasks, while human agents focus on empathy, complex decision‑making, and relationship‑building.
- Start with high‑impact journeys such as onboarding, collections, order updates and 24/7 support, where conversational AI can deliver visible ROI quickly and build internal confidence.
This approach is easy to adopt for businesses. For example, a leading bank or insurer can centralize customer profiles, transaction data, and risk signals on an AI‑first communications platform so that virtual agents can proactively remind customers about upcoming payments, trigger secure links for repayment or policy updates, and seamlessly escalate complex cases to human agents with full conversational and transactional context – improving recovery rates while reducing contact centre load.
Safeguarding conversations: fraud and security
As interactions become more conversational and distributed across channels, fraud prevention and security measures must be part of the design from day one. In banking and insurance, AI can help detect unusual behavior, flag suspicious requests, and enforce step‑up authentication when risk levels change – all without breaking the conversational flow. Verified business senders on WhatsApp and RCS, secure links, and robust consent management further reduce the risk of phishing and impersonation.
Both attackers and enterprises are scaling AI in parallel. As per our recent Fraud & Security Trends Report 2026, we have observed that while the adoption of AI‑powered fraud detection grew by71% year‑on‑year,AI‑driven fraud attempts rose by 77%. This reinforces the need for enterprises to embed intelligent security and fraud controls directly into their conversational journeys rather than treating them as bolt‑on safeguards.
Equally important is governance: clear escalation paths to human agents, transparent disclosure when customers are interacting with AI, and regular monitoring of models for bias and misuse are essential to sustaining trust. When customers feel that conversations are both helpful and secure, they are far more willing to engage and share the data that makes personalization possible.
AI‑powered conversations are growing to become the primary way enterprises in India connect, sell, and support across banking, insurance, retail, and beyond. Leaders who treat conversational AI as a strategic capability that is built on unified data, trusted automation, and a truly omnichannel platform will be the ones who close the effectiveness gap and define the next decade of customer experience.
The opportunity is not merely to automate communication, but to build stronger, long‑term customer relationships where every interaction, on every channel, can turn into a meaningful conversation.
DISCLAIMER: The views expressed are solely those of the author, and Adgully.com does not necessarily subscribe to them.
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AG Voice28-Aug-2026InfobipIndiaCountry HeadParitosh Gandhi
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